Brain-Computer Interfaces provide a method to connect the human brain to a computer, feeding thoughts from the subject to perform a task. Using EEG (electroencephalography), we ‘read’ the subject’s choice in regard to the motion of a robot. While the subject focuses on options for motion on his/her screen, the robot follows the choice and moves to the desired location. The subject sees the motion of the robot (often far away) on their screen, and can keep making choices until they ‘reach’ the desired location. Although currently targeted towards immobilized patients, such systems could potentially be the way we control the machines of the future.

Our research is on the development of a BCI-driven-robot: both the interface and the experiments to run it. We will discuss the interfacing mechanism, how well the robot can be controlled and our work on developing a better system of ‘reading’ the subject’s brain waves using artificial neural networks.

Sponsored by Lafayette Dean of The College, the Department of Computer Science, The Health and Life Science Program, Biotechnology/Bioengineering Program, and the National Science Foundation. Contact Person: Xiaoyan Li, Computer Science, lix@lafayette.edu, 610-330-5416

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